MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05.
8
Salary (millions of $)
Viewers (millions)
101
3
12
12
5.5
7.4
6.8
4.7
5.6
6.6
2.3
9.1
Click the icon to view the critical values of the Pearson correlation coefficient r.
What is the regression equation?
- X
Critical Values of the Pearson Correlation Coefficient r
y=+ x (Round to three decimal places as needed.)
What is the best predicted number of viewers for a television star with a salary of $2 million?
The best predicted number of viewers for a television star with a salary of $2 million is million.
Critical Values of the Pearson Correlation Coefficient r
NOTE: To test Ho: p=0
against H;: p# 0, reject H
if the absolute value of r is
greater than the critical
value in the table.
a= 0.05
= 0.01
n
(Round to one decimal place as needed.)
4
0.950
0.000
5
0.878
0.059
Is the result close to the actual number of viewers, 4.1 million?
0.811
0.017
7
0.754
0.875
O A. The result is not very close to the actual number of viewers of 4.1 million.
0.834
0.707
O B. The result is very close to the actual number of viewers of 4.1 million.
0.666
0.798
10
0.632
0.765
Oc. The result is exactly the same as the actual number of viewers of 4.1 million.
11
0.735
0.602
O D. The result does not make sense given the context of the data
12
0.576
0.708
13
0.553
0.684
14
0.532
0.601
15
0.514
0.641
16
0.497
0.623
17
0.482
0.606
18
0.468
0.590
0.575
0.561
19
0.456
20
0.444
25
30
35
40
0.396
0.505
0.361
0.483
0.335
0.430
0.312
0.402
45
0.294
0.378
50
0.279
0.361
60
0.254
0.330
70
0.236
0.305
80
0.220
0.286
0.207
0.196
a = 0.05
06
0.269
100
0.256
X = 0.01
n
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Transcribed Image Text:The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05. 8 Salary (millions of $) Viewers (millions) 101 3 12 12 5.5 7.4 6.8 4.7 5.6 6.6 2.3 9.1 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? - X Critical Values of the Pearson Correlation Coefficient r y=+ x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 million is million. Critical Values of the Pearson Correlation Coefficient r NOTE: To test Ho: p=0 against H;: p# 0, reject H if the absolute value of r is greater than the critical value in the table. a= 0.05 = 0.01 n (Round to one decimal place as needed.) 4 0.950 0.000 5 0.878 0.059 Is the result close to the actual number of viewers, 4.1 million? 0.811 0.017 7 0.754 0.875 O A. The result is not very close to the actual number of viewers of 4.1 million. 0.834 0.707 O B. The result is very close to the actual number of viewers of 4.1 million. 0.666 0.798 10 0.632 0.765 Oc. The result is exactly the same as the actual number of viewers of 4.1 million. 11 0.735 0.602 O D. The result does not make sense given the context of the data 12 0.576 0.708 13 0.553 0.684 14 0.532 0.601 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 0.575 0.561 19 0.456 20 0.444 25 30 35 40 0.396 0.505 0.361 0.483 0.335 0.430 0.312 0.402 45 0.294 0.378 50 0.279 0.361 60 0.254 0.330 70 0.236 0.305 80 0.220 0.286 0.207 0.196 a = 0.05 06 0.269 100 0.256 X = 0.01 n
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